EasyDCP: An affordable, high-throughput tool to measure plant phenotypic traits in 3D

Alexander Feldman, Haozhou Wang, Yuya Fukano, Yoichiro Kato, Seishi Ninomiya, Wei Guo

研究成果: ジャーナルへの寄稿学術誌査読

3 被引用数 (Scopus)

抄録

High-throughput 3D phenotyping is a rapidly emerging field that has widespread application for measurement of individual plants. Despite this, high-throughput plant phenotyping is rarely used in ecological studies due to financial and logistical limitations. We introduce EasyDCP, a Python package for 3D phenotyping, which uses photogrammetry to automatically reconstruct 3D point clouds of individuals within populations of container plants and output phenotypic trait data. Here we give instructions for the imaging setup and the required hardware, which is minimal and do-it-yourself, and introduce the functionality and workflow of EasyDCP. We compared the performance of EasyDCP against a high-end commercial laser scanner for the acquisition of plant height and projected leaf area. Both tools had strong correlations with ground truth measurement, and plant height measurements were more accurate using EasyDCP (plant height: EasyDCP r2 = 0.96, Laser r2 = 0.86; projected leaf area: EasyDCP r2 = 0.96, Laser r2 = 0.96). EasyDCP is an open-source software tool to measure phenotypic traits of container plants with high-throughput and low labour and financial costs.

本文言語英語
ページ(範囲)1679-1686
ページ数8
ジャーナルMethods in Ecology and Evolution
12
9
DOI
出版ステータス出版済み - 9月 2021
外部発表はい

!!!All Science Journal Classification (ASJC) codes

  • 生態、進化、行動および分類学
  • 生態モデリング

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